MEGA X: Molecular Evolutionary Genetics Analysis acrossComputing Platforms
Sudhir Kumar,†,1,2,3 Glen Stecher,†,1 Michael Li,1 Christina Knyaz,1 and Koichiro Tamura*,4,5
1Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
Department of Biology, Temple University, Philadelphia, PA
3Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah, Saudi Arabia
4
Research Center for Genomics and Bioinformatics, Tokyo Metropolitan University, Hachioji, Japan
5
Department of Biological Sciences, Tokyo Metropolitan University, Hachioji, Japan†Joint first authors.
*Corresponding author: E-mail: ktamura@tmu.ac.jp.
Associate editor: Fabia Ursula Battistuzzi
2Abstract
The Molecular Evolutionary Genetics Analysis (MEGA) software implements many analytical methods and tools forphylogenomics and phylomedicine. Here, we report a transformation of MEGA to enable cross-platform use on
Microsoft Windows and Linux operating systems. MEGA X does not require virtualization or emulation software andprovides a uniform user experience across platforms. MEGA X has additionally been upgraded to use multiple computing
cores for many molecular evolutionary analyses. MEGA X is available in two interfaces (graphical and command line) andcan be downloaded from www.megasoftware.net free of charge.
Key words: software, evolution, Linux.

Introduction

MEGA across Computing Platforms (MEGA X)MEGA was first developed for MS DOS in the early 1990s(Kumar et al. 1994) and then upgraded for use in MS
Windows eight times, including MEGA 1 to MEGA 6 andMEGA-CC and MEGA-MD (Kumar et al. 2001, 2016). Someof the MEGA releases have been packaged for Linux systems
using the WINE compatibility layer for POSIX-compliant operating systems and the Wineskin tool (built on WINE) formacOS systems. These versions have been downloaded over
200,000 times. But the ad hoc Windows-emulation solution issluggish and relatively unstable when compared with theCross-Platform Graphical User Interface (GUI)for MEGA X
The GUI has been programmed by refactoring MEGA’s sourcecode to be compatible with the Lazarus integrated development environment (Lazarus Team) and the Free Pascal compiler. Extensive reprogramming of visual components wasneeded to compile cross-platform MEGA, including theAlignment Explorer, Sequence Data Explorer, and Tree
Explorer. Additionally, all the internal control code thatused the MS Windows system application programming interface (API) was advanced to work across platforms.
The reprogramming was accompanied with visual modernization of many parts of the GUI (fig. 1). To provide a
uniform user experience across computing platforms, many
user interface elements have been implemented using theChromium Embedded Framework (CEF), which is an open
source framework based on the Google Chromium web

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Brief Communication

Over the past decade, genome sequencing has become an
efficient and potent means to investigate a broad array of
biological systems, from large-scale studies of biological diversity to tracking the evolution and origin of pathogenic
microbes. The numerous steps required to glean interpretable
and actionable results from raw sequence data invariably require comparative analysis of molecular sequences to discoverfunctional and adaptive genome differences. Molecular
Evolutionary Genetics Analysis (MEGA) software provides tools
to conduct such analyses. MEGA includes a large repertoire ofprograms for assembling sequence alignments, inferring evolutionary trees, estimating genetic distances and diversities,
inferring ancestral sequences, computing timetrees, and testing selection (Kumar et al. 2016). Over the last 25 years, MEGA’s
use in evolutionary analysis has been cited in over one hundred thousand studies in diverse biological fields.

performance in MS Windows. Emulators cannot be used effectively for the latest 64-bit version of MEGA that is built tohandle memory-intensive analyses of large contemporary
data sets (Kumar et al. 2016), so a more comprehensive solution is required for users of alternate platforms.
Therefore, MEGA has been transformed into a crossplatform version that runs natively on Linux and Microsoft
Windows. This advancement eliminates the Windows-only
limitation of MEGA, which has become particularly acute dueto the increasing use of Linux in biological research. Thistransformation also paves the way for development of aMEGA X version for macOS in the near future.

Kumar et al. . doi:10.1093/molbev/msy096

MBEFIG. 1. The MEGA X main form has a modernized look-and-feel, but it maintains the familiar structure of the previous versions of MEGA. (A) The top
toolbar organizes the large number of analyses available in MEGA X into logical groups accessed via drop down menus. (B) The bottom toolbar
provides access to utility functions such as the help system, example input data files and application preferences. (C) Icons on the main form
provide convenient access to input data and results explorer windows. Mega X can now be used in two modes: one for data analysis (ANALYZEmode) and another for prototyping (PROTOTYPE mode).

browser core. With this framework, we have implemented
GUI elements using HTML and JavaScript in MEGA X desktop
GUI (fig. 2). As a result, MEGA X has the same look-and-feel in
Windows and Linux. We are currently developing MEGA X formacOS, which will share this user interface.

Parallelization of Computational Core
We have also improved MEGA’s computational core by increasing the number of methods that can utilize multiple
processors and cores on the same machine. This will greatly
reduce the run time for computationally demanding inferences. Users can specify the maximum number of cores todeploy in the Analysis Preferences dialog box (fig. 2G). By
default, MEGA X uses all available cores, minus one, suchthat no >80% of RAM is consumed. Computational methods
benefitting from calculation parallelization include those forselecting the best model for nucleotide or amino acid substitutions and bootstrap tests of molecular phylogenies
employed with distance-based and parsimony-based methods. Users can already employ multiple cores during the heuristic search for the Maximum Likelihood (ML) tree in MEGA.

Distributions
On Microsoft Windows, MEGA X is intended to be used on 64bit systems having version 10 and later. It will, however, worksmoothly on previous versions of 64-bit Windows. We also
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on 24 May 2018provide a 32-bit version of MEGA X for Windows for thosewith 32-bit computers. On Linux platforms, MEGA X has been
optimized and tested for use on Debian/Ubuntu and RedHat/
CentOS based distributions. Because users may customize
their Linux environments easily, we recommend use of
MEGA X for Linux in tested desktop environments.
Specifically, we have tested MEGA X on Ubuntu 16.04.4(with Unity desktop), Mint 18.1 (with Cinnamon desktop),and CentOS 7 (with GNOME desktop).
MEGA X now generates a configuration file specifying analysis options for user-desired analysis in MEGA CC, which many
researchers use for high throughput and iterative analysis in
Windows, Linux and macOS environments (Kumar et al.
2012). The “Save Settings” button provides this functionality(fig. 2H). In fact, MEGA X can now be used in the prototypemode (see fig. 1, lower right corner), if desired, which obviates
the need to distribute and maintain a separate application forgenerating the configuration file for running MEGA CC, so
MEGA-Proto is no longer required or supported.
In conclusion, the cross-platform MEGA X will benefit many
existing users and enable many others to consider utilizing
MEGA X in their research and teaching endeavors. The consistency of user experience across platforms should be particularly useful in facilitating collaborative analyses withinand among research groups as well as in teaching a diverse
group of students. In the near future, we will complete theMolecular Evolutionary Genetics Analysis across Computing Platforms . doi:10.1093/molbev/msy096

MBEFIG. 2. The redesigned GUI elements in MEGA X include explorer windows such as the (A) Sequence Data Explorer, (B) Timetree Wizard, and (C)Tree Explorer. These use the native widget set of the target operating system. (D) Options dialogs and (E) Caption Expert were developed using
HTML and JavaScript and are displayed via MEGA’s integrated web browser that is built on the Chromium Embedded Framework. (F) The
redesigned “Analysis Preferences” dialog box for selecting options for data analysis, including (G) the number of threads to employ and (H) a“Save Settings” button for generating an “.mao” file for use with MEGA-CC for high throughput analysis.

development of a macOS version to make MEGA X available
for all major operating systems.

Acknowledgments
We thank our laboratory members and many beta testers
for providing invaluable feedback and bug reports. This
work was supported in part by research grants fromNational Institutes of Health (R01GM126567-01),
National Science Foundation (ABI 1661218) to S.K., andJapan Society for the Promotion of Science (JSPS) grantsin-aid for scientific research (DB5) to K.T.

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References
Kumar S, Stecher G, Peterson D, Tamura K. 2012. MEGA-CC: computing
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Kumar S, Stecher G, Tamura K. 2016. MEGA7: molecular evolutionarygenetics analysis version 7.0 for bigger datasets. Mol Biol Evol.
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Kumar S, Tamura K, Jakobsen IB, Nei M. 2001. MEGA2: molecular evolutionary genetics analysis software. Bioinformatics 17(12):1244–1245.
Kumar S, Tamura K, Nei M. 1994. MEGA: molecular EvolutionaryGenetics Analysis software for microcomputers. Comput Appl
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Lazarus Team. Lazarus Homepage. Available from: https://www.lazaruside.org/.

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